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Consider the following valuation factors of a company: It owns 1000 cars valued at $50,000 each It holds real estate worth $15,000,000 It owes $5,000,000 in loans It pays $3.00 per year per share in dividends starting in one year The stock price is $40.00 per share There are 1,000,000 shares outstanding The discount rate is 5% Suppose you believe that over a period of a few weeks, the price of the stock will converge to book value + 10%.  What should you do to profit from this expectation?

Consider the following Python session and its output. >>> import numpy as np >>> a = np.random.uniform(size=(5, 9)) >>> b = a/a[3, :] >>> print(XXXX) 1.0 What should you replace XXXX with in order to get the following output?

Consider overfitting when using DTLearner and a polynomial KNN. When overfitting occurs with these two methods, in which “direction” does it occur?

Consider kNN, linear regression (LR), Decision tree (DT) learning (using correlation for splitting), and Random tree. Which model has the slowest in query time?

What is the output of the following Python code snippet? >>> import numpy as np >>> np.random.seed(5) >>> x = np.random.uniform(0, 4) >>> np.random.seed(5) >>> y = np.random.uniform(0, 4) >>> z = np.random.uniform(0, 4) >>> print(z == y, x == z)

What is the output of the following Python session? >>> def func(k = 4): … j = 8 … return k + j … >>> q = 7 >>> j = 3 >>> print(func())

Consider the following order book. Bid size Price Ask size 200.80 300 200.75 200 200.50 100 200.25 100 100 199.95 400 199.90 100 199.85 At what average price would a limit order to BUY 200 shares at $200.75 be executed?

What is the output of the following Python session? >>> x = 5 >>> y = x >>> x = 3 >>> print(y * x)

Which of the following is NOT an advantage of ensemble learners?

Consider the following order book. Bid size Price Ask size 55.90 400 55.85 300 55.75 300 100 55.45 75 55.35 200 55.25 At what average price would a market order to BUY 100 shares be executed?